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The interplay between Steinberg algebras and partial skew rings
We study the interplay between Steinberg algebras and partial skew rings: For a partial action of a group in a Hausdorff, locally compact, totally disconnected topological space, we realize the associated partial skew group ring as a Steinberg algebra (over the transformation groupoid attached to the partial action)....
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Type-II Dirac Photons
The Dirac equation for relativistic electron waves is the parent model for Weyl and Majorana fermions as well as topological insulators. Simulation of Dirac physics in three-dimensional photonic crystals, though fundamentally important for topological phenomena at optical frequencies, encounters the challenge of synt...
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Improving Network Robustness against Adversarial Attacks with Compact Convolution
Though Convolutional Neural Networks (CNNs) have surpassed human-level performance on tasks such as object classification and face verification, they can easily be fooled by adversarial attacks. These attacks add a small perturbation to the input image that causes the network to misclassify the sample. In this paper,...
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From sudden quench to adiabatic dynamics in the attractive Hubbard model
We study the crossover between the sudden quench limit and the adiabatic dynamics of superconducting states in the attractive Hubbard model. We focus on the dynamics induced by the change of the attractive interaction during a finite ramp time which is varied in order to track the evolution of the dynamical phase dia...
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Strongly exchange-coupled and surface-state-modulated magnetization dynamics in Bi2Se3/YIG heterostructures
We report strong interfacial exchange coupling in Bi2Se3/yttrium iron garnet (YIG) bilayers manifested as large in-plane interfacial magnetic anisotropy (IMA) and enhancement of damping probed by ferromagnetic resonance (FMR). The IMA and spin mixing conductance reached a maximum when Bi2Se3 was around 6 quintuple-la...
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Survivable Probability of SDN-enabled Cloud Networking with Random Physical Link Failure
Software-driven cloud networking is a new paradigm in orchestrating physical resources (CPU, network bandwidth, energy, storage) allocated to network functions, services, and applications, which is commonly modeled as a cross-layer network. This model carries a physical network representing the physical infrastructur...
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Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers
PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in practice. In this paper, we extend PILCO, a model-based policy search framework, to automatically tune multivariate PID controllers purely b...
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Engineering a Simplified 0-Bit Consistent Weighted Sampling
The Min-Hashing approach to sketching has become an important tool in data analysis, information retrial, and classification. To apply it to real-valued datasets, the ICWS algorithm has become a seminal approach that is widely used, and provides state-of-the-art performance for this problem space. However, ICWS suffe...
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Quantifying macroeconomic expectations in stock markets using Google Trends
Among other macroeconomic indicators, the monthly release of U.S. unemployment rate figures in the Employment Situation report by the U.S. Bureau of Labour Statistics gets a lot of media attention and strongly affects the stock markets. I investigate whether a profitable investment strategy can be constructed by pred...
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Effects of Incomplete Ionization on Beta - Ga2O3 Power Devices: Unintentional Donor with Energy 110 meV
Understanding the origin of unintentional doping in Ga2O3 is key to increasing breakdown voltages of Ga2O3 based power devices. Therefore, transport and capacitance spectroscopy studies have been performed to better understand the origin of unintentional doping in Ga2O3. Previously unobserved unintentional donors in ...
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A single coordinate framework for optic flow and binocular disparity
Optic flow is two dimensional, but no special qualities are attached to one or other of these dimensions. For binocular disparity, on the other hand, the terms 'horizontal' and 'vertical' disparities are commonly used. This is odd, since binocular disparity and optic flow describe essentially the same thing. The diff...
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Gain control with A-type potassium current: IA as a switch between divisive and subtractive inhibition
Neurons process information by transforming barrages of synaptic inputs into spiking activity. Synaptic inhibition suppresses the output firing activity of a neuron, and is commonly classified as having a subtractive or divisive effect on a neuron's output firing activity. Subtractive inhibition can narrow the range ...
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Cyclic Datatypes modulo Bisimulation based on Second-Order Algebraic Theories
Cyclic data structures, such as cyclic lists, in functional programming are tricky to handle because of their cyclicity. This paper presents an investigation of categorical, algebraic, and computational foundations of cyclic datatypes. Our framework of cyclic datatypes is based on second-order algebraic theories of F...
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High-order harmonic generation from highly-excited states in acetylene
High-order harmonic generation (HHG) from aligned acetylene molecules interacting with mid infra-red (IR), linearly polarized laser pulses is studied theoretically using a mixed quantum-classical approach in which the electrons are described using time-dependent density functional theory while the ions are treated cl...
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Cellulyzer - Automated analysis and interactive visualization/simulation of select cellular processes
Here we report on a set of programs developed at the ZMBH Bio-Imaging Facility for tracking real-life images of cellular processes. These programs perform 1) automated tracking; 2) quantitative and comparative track analyses of different images in different groups; 3) different interactive visualization schemes; and ...
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Vprop: Variational Inference using RMSprop
Many computationally-efficient methods for Bayesian deep learning rely on continuous optimization algorithms, but the implementation of these methods requires significant changes to existing code-bases. In this paper, we propose Vprop, a method for Gaussian variational inference that can be implemented with two minor...
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Hidden symmetries in $N$-layer dielectric stacks
The optical properties of a multilayer system of dielectric media with arbitrary $N$ layers is investigated. Each layer is one of two dielectric media, with thickness one-quarter the wavelength of light in that medium, corresponding to a central frequency. Using the transfer matrix method, the transmittance $T$ is ca...
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Solvability regions of affinely parameterized quadratic equations
Quadratic systems of equations appear in several applications. The results in this paper are motivated by quadratic systems of equations that describe equilibrium behavior of physical infrastructure networks like the power and gas grids. The quadratic systems in infrastructure networks are parameterized- the paramete...
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Mid-price estimation for European corporate bonds: a particle filtering approach
In most illiquid markets, there is no obvious proxy for the market price of an asset. The European corporate bond market is an archetypal example of such an illiquid market where mid-prices can only be estimated with a statistical model. In this OTC market, dealers / market makers only have access, indeed, to partial...
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Matching RGB Images to CAD Models for Object Pose Estimation
We propose a novel method for 3D object pose estimation in RGB images, which does not require pose annotations of objects in images in the training stage. We tackle the pose estimation problem by learning how to establish correspondences between RGB images and rendered depth images of CAD models. During training, our...
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A Model for Paired-Multinomial Data and Its Application to Analysis of Data on a Taxonomic Tree
In human microbiome studies, sequencing reads data are often summarized as counts of bacterial taxa at various taxonomic levels specified by a taxonomic tree. This paper considers the problem of analyzing two repeated measurements of microbiome data from the same subjects. Such data are often collected to assess the ...
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Adhesion-induced Discontinuous Transitions and Classifying Social Networks
Transition points mark qualitative changes in the macroscopic properties of large complex systems. Explosive transitions, exhibiting properties of both continuous and discontinuous phase transitions, have recently been uncovered in network growth processes. Real networks not only grow but often also restructure, yet ...
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Numerical simulation of polynomial-speed convergence phenomenon
We provide a hybrid method that captures the polynomial speed of convergence and polynomial speed of mixing for Markov processes. The hybrid method that we introduce is based on the coupling technique and renewal theory. We propose to replace some estimates in classical results about the ergodicity of Markov processe...
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Efficient determination of optimised multi-arm multi-stage experimental designs with control of generalised error-rates
Primarily motivated by the drug development process, several publications have now presented methodology for the design of multi-arm multi-stage experiments with normally distributed outcome variables of known variance. Here, we extend these past considerations to allow the design of what we refer to as an abcd multi...
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Application of the Waveform Relaxation Technique to the Co-Simulation of Power Converter Controller and Electrical Circuit Models
In this paper we present the co-simulation of a PID class power converter controller and an electrical circuit by means of the waveform relaxation technique. The simulation of the controller model is characterized by a fixed-time stepping scheme reflecting its digital implementation, whereas a circuit simulation usua...
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Some Investigations about the Properties of Maximum Likelihood Estimations Based on Lower Record Values for a Sub-Family of the Exponential Family
Here, in this paper it has been considered a sub family of exponential family. Maximum likelihood estimations (MLE) for the parameter of this family, probability density function, and cumulative density function based on a sample and based on lower record values have been obtained. It has been considered Mean Square ...
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Some Insights on Synthesizing Optimal Linear Quadratic Controller Using Krotov's Sufficiency Conditions
This paper revisits the problem of optimal control law design for linear systems using the global optimal control framework introduced by Vadim Krotov. Krotov's approach is based on the idea of total decomposition of the original optimal control problem (OCP) with respect to time, by an $ad$ $hoc$ choice of the so-ca...
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Schumann resonance transients and the search for gravitational waves
Schumann resonance transients which propagate around the globe can potentially generate a correlated background in widely separated gravitational wave detectors. We show that due to the distribution of lightning hotspots around the globe these transients have characteristic time lags, and this feature can be useful t...
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Learning to Fly by Crashing
How do you learn to navigate an Unmanned Aerial Vehicle (UAV) and avoid obstacles? One approach is to use a small dataset collected by human experts: however, high capacity learning algorithms tend to overfit when trained with little data. An alternative is to use simulation. But the gap between simulation and real w...
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Estimating Graphlet Statistics via Lifting
Exploratory analysis over network data is often limited by our ability to efficiently calculate graph statistics, which can provide a model-free understanding of macroscopic properties of a network. This work introduces a framework for estimating the graphlet count - the number of occurrences of a small subgraph moti...
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Calibration for the (Computationally-Identifiable) Masses
As algorithms increasingly inform and influence decisions made about individuals, it becomes increasingly important to address concerns that these algorithms might be discriminatory. The output of an algorithm can be discriminatory for many reasons, most notably: (1) the data used to train the algorithm might be bias...
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The distribution of old stars around the Milky Way's central black hole I: Star counts
(abridged) In this paper we revisit the problem of inferring the innermost structure of the Milky Way's nuclear star cluster via star counts, to clarify whether it displays a core or a cusp around the central black hole. Through image stacking and improved PSF fitting we push the completeness limit about one magnitud...
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On infinite order differential operators in fractional viscoelasticity
In this paper we discuss some general properties of viscoelastic models defined in terms of constitutive equations involving infinitely many derivatives (of integer and fractional order). In particular, we consider as a working example the recently developed Bessel models of linear viscoelasticiy that, for short time...
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Gap structure of FeSe determined by field-angle-resolved specific heat measurements
Quasiparticle excitations in FeSe were studied by means of specific heat ($C$) measurements on a high-quality single crystal under rotating magnetic fields. The field dependence of $C$ shows three-stage behavior with different slopes, indicating the existence of three gaps ($\Delta_1$, $\Delta_2$, and $\Delta_3$). In...
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Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets
This paper presents a model based on Deep Learning algorithms of LSTM and GRU for facilitating an anomaly detection in Large Hadron Collider superconducting magnets. We used high resolution data available in Post Mortem database to train a set of models and chose the best possible set of their hyper-parameters. Using...
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Electro-Oxidation of Ni42 Steel: A highly Active Bifunctional Electrocatalyst
Janus type Water-Splitting Catalysts have attracted highest attention as a tool of choice for solar to fuel conversion. AISI Ni 42 steel was upon harsh anodization converted in a bifunctional electrocatalyst. Oxygen evolution reaction- (OER) and hydrogen evolution reaction (HER) are highly efficiently and steadfast c...
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Shape-constrained partial identification of a population mean under unknown probabilities of sample selection
A prevailing challenge in the biomedical and social sciences is to estimate a population mean from a sample obtained with unknown selection probabilities. Using a well-known ratio estimator, Aronow and Lee (2013) proposed a method for partial identification of the mean by allowing the unknown selection probabilities ...
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Warped metrics for location-scale models
This paper argues that a class of Riemannian metrics, called warped metrics, plays a fundamental role in statistical problems involving location-scale models. The paper reports three new results : i) the Rao-Fisher metric of any location-scale model is a warped metric, provided that this model satisfies a natural inv...
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Detecting Changes in Time Series Data using Volatility Filters
This work develops techniques for the sequential detection and location estimation of transient changes in the volatility (standard deviation) of time series data. In particular, we introduce a class of change detection algorithms based on the windowed volatility filter. The first method detects changes by employing ...
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A minimax and asymptotically optimal algorithm for stochastic bandits
We propose the kl-UCB ++ algorithm for regret minimization in stochastic bandit models with exponential families of distributions. We prove that it is simultaneously asymptotically optimal (in the sense of Lai and Robbins' lower bound) and minimax optimal. This is the first algorithm proved to enjoy these two propert...
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Eigenfunctions of Periodic Differential Operators Analytic in a Strip
Ordinary differential operators with periodic coefficients analytic in a strip act on a Hardy-Hilbert space of analytic functions with inner product defined by integration over a period on the boundary of the strip. Simple examples show that eigenfunctions may form a complete set for a narrow strip, but completeness ...
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Infinite ergodic index of the ehrenfest wind-tree model
The set of all possible configurations of the Ehrenfest wind-tree model endowed with the Hausdorff topology is a compact metric space. For a typical configuration we show that the wind-tree dynamics has infinite ergodic index in almost every direction. In particular some ergodic theorems can be applied to show that i...
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Arrays of strongly-coupled atoms in a one-dimensional waveguide
We study the cooperative optical coupling between regularly spaced atoms in a one-dimensional waveguide using decompositions to subradiant and superradiant collective excitation eigenmodes, direct numerical solutions, and analytical transfer-matrix methods. We illustrate how the spectrum of transmitted light through ...
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MEG-Derived Functional Tractography, Results for Normal and Concussed Cohorts
Measures of neuroelectric activity from each of 18 automatically identified white matter tracts were extracted from resting MEG recordings from a normative, n=588, and a chronic TBI, traumatic brain injury, n=63, cohort, 60 of whose TBIs were mild. Activity in the TBI cohort was significantly reduced compared with th...
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Coincidence of magnetic and valence quantum critical points in CeRhIn5 under pressure
We present accurate electrical resistivity measurements along the two principle crystallographic axes of the pressure-induced heavy-fermion superconductor CeRhIn5 up to 5.63 GPa. For both directions, a valence crossover line is identified in the p-T plane and the extrapolation of this line to zero temperature coincid...
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Sequential Inverse Approximation of a Regularized Sample Covariance Matrix
One of the goals in scaling sequential machine learning methods pertains to dealing with high-dimensional data spaces. A key related challenge is that many methods heavily depend on obtaining the inverse covariance matrix of the data. It is well known that covariance matrix estimation is problematic when the number o...
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Sesqui-arrays, a generalisation of triple arrays
A triple array is a rectangular array containing letters, each letter occurring equally often with no repeats in rows or columns, such that the number of letters common to two rows, two columns, or a row and a column are (possibly different) non-zero constants. Deleting the condition on the letters common to a row an...
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Investigating how well contextual features are captured by bi-directional recurrent neural network models
Learning algorithms for natural language processing (NLP) tasks traditionally rely on manually defined relevant contextual features. On the other hand, neural network models using an only distributional representation of words have been successfully applied for several NLP tasks. Such models learn features automatica...
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A Hybridizable Discontinuous Galerkin solver for the Grad-Shafranov equation
In axisymmetric fusion reactors, the equilibrium magnetic configuration can be expressed in terms of the solution to a semi-linear elliptic equation known as the Grad-Shafranov equation, the solution of which determines the poloidal component of the magnetic field. When the geometry of the confinement region is known...
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Sketching Linear Classifiers over Data Streams
We introduce a new sub-linear space sketch---the Weight-Median Sketch---for learning compressed linear classifiers over data streams while supporting the efficient recovery of large-magnitude weights in the model. This enables memory-limited execution of several statistical analyses over streams, including online fea...
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Tamed to compatible when b^(2+) = 1 and b^1 = 2
Weiyi Zhang noticed recently a gap in the proof of the main theorem of the authors article "Tamed to compatible: Symplectic forms via moduli space integration" [T] for the case when the symplectic 4-manifold in question has first Betti number 2 (and necessarily self-dual second Betti number 1). This note explains how...
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The Mass Transference Principle: Ten Years On
In this article we discuss the Mass Transference Principle due to Beresnevich and Velani and survey several generalisations and variants, both deterministic and random. Using a Hausdorff measure analogue of the inhomogeneous Khintchine-Groshev Theorem, proved recently via an extension of the Mass Transference Princip...
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Ground-state properties of Ca$_2$ from narrow line two-color photoassociation
By two-color photoassociation of $^{40}$Ca four weakly bound vibrational levels in the Ca$_2$ \Xpot ground state potential were measured, using highly spin-forbidden transitions to intermediate states of the coupled system $^3\Pi_{u}$ and $^3\Sigma^+ _{u}$ near the ${^3P_1}$+${^1S_0}$ asymptote. From the observed bin...
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On the semisimplicity of the cyclotomic quiver Hecke algebra of type C
We provide criteria for the cyclotomic quiver Hecke algebras of type C to be semisimple. In the semisimple case, we construct the irreducible modules.
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On the origin of the shallow and "replica" bands in FeSe monolayer superconductors
We compare electronic structures of single FeSe layer films on SrTiO$_3$ substrate (FeSe/STO) and K$_x$Fe$_{2-y}$Se$_{2}$ superconductors obtained from extensive LDA and LDA+DMFT calculations with the results of ARPES experiments. It is demonstrated that correlation effects on Fe-3d states are sufficient in principle...
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A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers
Regularization techniques are widely employed in optimization-based approaches for solving ill-posed inverse problems in data analysis and scientific computing. These methods are based on augmenting the objective with a penalty function, which is specified based on prior domain-specific expertise to induce a desired ...
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A Bootstrap Method for Goodness of Fit and Model Selection with a Single Observed Network
Network models are applied in numerous domains where data can be represented as a system of interactions among pairs of actors. While both statistical and mechanistic network models are increasingly capable of capturing various dependencies amongst these actors, these dependencies imply the lack of independence. This...
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Nonlinear Acceleration of Stochastic Algorithms
Extrapolation methods use the last few iterates of an optimization algorithm to produce a better estimate of the optimum. They were shown to achieve optimal convergence rates in a deterministic setting using simple gradient iterates. Here, we study extrapolation methods in a stochastic setting, where the iterates are...
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Motion of Massive Particles in Rindler Space and the Problem of Fall at the Centre
The motion of a massive particle in Rindler space has been studied and obtained the geodesics of motion. The orbits in Rindler space are found to be quite different from that of Schwarzschild case. The paths are not like the Perihelion Precession type. Further we have set up the non-relativistic Schrodinger equation ...
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Measuring Sample Quality with Kernels
Approximate Markov chain Monte Carlo (MCMC) offers the promise of more rapid sampling at the cost of more biased inference. Since standard MCMC diagnostics fail to detect these biases, researchers have developed computable Stein discrepancy measures that provably determine the convergence of a sample to its target di...
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Diversity of preferences can increase collective welfare in sequential exploration problems
In search engines, online marketplaces and other human-computer interfaces large collectives of individuals sequentially interact with numerous alternatives of varying quality. In these contexts, trial and error (exploration) is crucial for uncovering novel high-quality items or solutions, but entails a high cost for...
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Epidemic spread in interconnected directed networks
In the real world, many complex systems interact with other systems. In addition, the intra- or inter-systems for the spread of information about infectious diseases and the transmission of infectious diseases are often not random, but with direction. Hence, in this paper, we build epidemic model based on an intercon...
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Controllability and maximum matchings of complex networks
Previously, the controllability problem of a linear time-invariant dynamical system was mapped to the maximum matching (MM) problem on the bipartite representation of the underlying directed graph, and the sizes of MMs on random bipartite graphs were calculated analytically with the cavity method at zero temperature ...
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Dimers, crystals and quantum Kostka numbers
We relate the counting of honeycomb dimer configurations on the cylinder to the counting of certain vertices in Kirillov-Reshetikhin crystal graphs. We show that these dimer configurations yield the quantum Kostka numbers of the small quantum cohomology ring of the Grassmannian, i.e. the expansion coefficients when m...
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Generalized Task-Parameterized Skill Learning
Programming by demonstration has recently gained much attention due to its user-friendly and natural way to transfer human skills to robots. In order to facilitate the learning of multiple demonstrations and meanwhile generalize to new situations, a task-parameterized Gaussian mixture model (TP-GMM) has been recently...
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Nonparametric Bayesian volatility learning under microstructure noise
Aiming at financial applications, we study the problem of learning the volatility under market microstructure noise. Specifically, we consider noisy discrete time observations from a stochastic differential equation and develop a novel computational method to learn the diffusion coefficient of the equation. We take a...
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Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained with Noise Signals
Supervised learning based methods for source localization, being data driven, can be adapted to different acoustic conditions via training and have been shown to be robust to adverse acoustic environments. In this paper, a convolutional neural network (CNN) based supervised learning method for estimating the directio...
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Follow-up of eROSITA and Euclid Galaxy Clusters with XMM-Newton
A revolution in galaxy cluster science is only a few years away. The survey machines eROSITA and Euclid will provide cluster samples of never-before-seen statistical quality. XMM-Newton will be the key instrument to exploit these rich datasets in terms of detailed follow-up of the cluster hot gas content, systematica...
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Effect of viscosity ratio on the self-sustained instabilities in planar immiscible jets
Previous studies have shown that intermediate surface tension has a counterintuitive destabilizing effect on 2-phase planar jets. Here, the transition process in confined 2D jets of two fluids with varying viscosity ratio is investigated using DNS. Neutral curves for persistent oscillations are found by recording the...
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On the Effects of Batch and Weight Normalization in Generative Adversarial Networks
Generative adversarial networks (GANs) are highly effective unsupervised learning frameworks that can generate very sharp data, even for data such as images with complex, highly multimodal distributions. However GANs are known to be very hard to train, suffering from problems such as mode collapse and disturbing visu...
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A noise-immune cavity-assisted non-destructive detection for an optical lattice clock in the quantum regime
We present and implement a non-destructive detection scheme for the transition probability readout of an optical lattice clock. The scheme relies on a differential heterodyne measurement of the dispersive properties of lattice-trapped atoms enhanced by a high finesse cavity. By design, this scheme offers a 1st order ...
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Remarks on planar edge-chromatic critical graphs
The only open case of Vizing's conjecture that every planar graph with $\Delta\geq 6$ is a class 1 graph is $\Delta = 6$. We give a short proof of the following statement: there is no 6-critical plane graph $G$, such that every vertex of $G$ is incident to at most three 3-faces. A stronger statement without restricti...
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The LOFAR window on star-forming galaxies and AGN - curved radio SEDs and IR-radio correlation at $0 < z < 2.5$
We present a study of the low-frequency radio properties of star forming (SF) galaxies and active galactic nuclei (AGN) up to redshift $z=2.5$. The new spectral window probed by the Low Frequency Array (LOFAR) allows us to reconstruct the radio continuum emission from 150 MHz to 1.4 GHz to an unprecedented depth for ...
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Interplay between the Inverse Scattering Method and Fokas's Unified Transform with an Application
It is known that the initial-boundary value problem for certain integrable partial differential equations (PDEs) on the half-line with integrable boundary conditions can be mapped to a special case of the Inverse Scattering Method (ISM) on the full-line. This can also be established within the so-called Unified Trans...
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GNC of the SphereX Robot for Extreme Environment Exploration on Mars
Wheeled ground robots are limited from exploring extreme environments such as caves, lava tubes and skylights. Small robots that can utilize unconventional mobility through hopping, flying or rolling can overcome these limitations. Mul-tiple robots operating as a team offer significant benefits over a single large ro...
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Stable Signatures for Dynamic Graphs and Dynamic Metric Spaces via Zigzag Persistence
When studying flocking/swarming behaviors in animals one is interested in quantifying and comparing the dynamics of the clustering induced by the coalescence and disbanding of animals in different groups. In a similar vein, studying the dynamics of social networks leads to the problem of characterizing groups/communi...
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A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space
We are developing a system for human-robot communication that enables people to communicate with robots in a natural way and is focused on solving problems in a shared space. Our strategy for developing this system is fundamentally data-driven: we use data from multiple input sources and train key components with var...
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Discursive Landscapes and Unsupervised Topic Modeling in IR: A Validation of Text-As-Data Approaches through a New Corpus of UN Security Council Speeches on Afghanistan
The recent turn towards quantitative text-as-data approaches in IR brought new ways to study the discursive landscape of world politics. Here seen as complementary to qualitative approaches, quantitative assessments have the advantage of being able to order and make comprehensible vast amounts of text. However, the v...
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Lattice Gas with Molecular Dynamics Collision Operator
We introduce a lattice gas implementation that is based on coarse-graining a Molecular Dynamics (MD) simulation. Such a lattice gas is similar to standard lattice gases, but its collision operator is informed by an underlying MD simulation. This can be considered an optimal lattice gas implementation because it allow...
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From dynamical systems with time-varying delay to circle maps and Koopmanism
In the present paper we investigate the influence of the retarded access by a time-varying delay on the dynamics of delay systems. We show that there are two universality classes of delays, which lead to fundamental differences in dynamical quantities such as the Lyapunov spectrum. Therefore we introduce an operator ...
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Engineering Frequency-dependent Superfluidity in Bose-Fermi Mixtures
Unconventional superconductivity or superfluidity are among the most exciting and fascinating quantum states in condensed matter physics. Usually these states are characterized by non-trivial spatial symmetry of the pairing order parameter, such as in $^{3}He$ and high-$T_{c}$ cuprates. Besides spatial dependence the...
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In-Silico Proportional-Integral Moment Control of Stochastic Reaction Networks with Applications to Gene Expression (with Dimerization)
The problem of controlling the mean and the variance of a species of interest in a simple gene expression is addressed. It is shown that the protein mean level can be globally and robustly tracked to any desired value using a simple PI controller that satisfies certain sufficient conditions. Controlling both the mean...
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Big enterprise registration data imputation: Supporting spatiotemporal analysis of industries in China
Big, fine-grained enterprise registration data that includes time and location information enables us to quantitatively analyze, visualize, and understand the patterns of industries at multiple scales across time and space. However, data quality issues like incompleteness and ambiguity, hinder such analysis and appli...
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Fast Simulation of Vehicles with Non-deformable Tracks
This paper presents a novel technique that allows for both computationally fast and sufficiently plausible simulation of vehicles with non-deformable tracks. The method is based on an effect we have called Contact Surface Motion. A comparison with several other methods for simulation of tracked vehicle dynamics is pr...
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Persistent Hidden States and Nonlinear Transformation for Long Short-Term Memory
Recurrent neural networks (RNNs) have been drawing much attention with great success in many applications like speech recognition and neural machine translation. Long short-term memory (LSTM) is one of the most popular RNN units in deep learning applications. LSTM transforms the input and the previous hidden states t...
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Satellite Image-based Localization via Learned Embeddings
We propose a vision-based method that localizes a ground vehicle using publicly available satellite imagery as the only prior knowledge of the environment. Our approach takes as input a sequence of ground-level images acquired by the vehicle as it navigates, and outputs an estimate of the vehicle's pose relative to a...
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Optimality of codes with respect to error probability in Gaussian noise
We consider geometrical optimization problems related to optimizing the error probability in the presence of a Gaussian noise. One famous questions in the field is the "weak simplex conjecture". We discuss possible approaches to it, and state related conjectures about the Gaussian measure, in particular, the conjectu...
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Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs
Time delay neural networks (TDNNs) are an effective acoustic model for large vocabulary speech recognition. The strength of the model can be attributed to its ability to effectively model long temporal contexts. However, current TDNN models are relatively shallow, which limits the modelling capability. This paper pro...
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A Structured Self-attentive Sentence Embedding
This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention. Instead of using a vector, we use a 2-D matrix to represent the embedding, with each row of the matrix attending on a different part of the sentence. We also propose a self-attention mechanism and a speci...
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When Neurons Fail
We view a neural network as a distributed system of which neurons can fail independently, and we evaluate its robustness in the absence of any (recovery) learning phase. We give tight bounds on the number of neurons that can fail without harming the result of a computation. To determine our bounds, we leverage the fa...
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Heavy Traffic Limit for a Tandem Queue with Identical Service Times
We consider a two-node tandem queueing network in which the upstream queue is M/G/1 and each job reuses its upstream service requirement when moving to the downstream queue. Both servers employ the first-in-first-out policy. We investigate the amount of work in the second queue at certain embedded arrival time points...
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Autonomous Sweet Pepper Harvesting for Protected Cropping Systems
In this letter, we present a new robotic harvester (Harvey) that can autonomously harvest sweet pepper in protected cropping environments. Our approach combines effective vision algorithms with a novel end-effector design to enable successful harvesting of sweet peppers. Initial field trials in protected cropping env...
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AMI SZ observation of galaxy-cluster merger CIZA J2242+5301: perpendicular flows of gas and dark matter
AMI observations towards CIZA J2242+5301, in comparison with observations of weak gravitational lensing and X-ray emission from the literature, are used to investigate the behaviour of non-baryonic dark matter (NBDM) and gas during the merger. Analysis of the Sunyaev-Zel'dovich (SZ) signal indicates the presence of h...
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Development of a computer-aided design software for dental splint in orthognathic surgery
In the orthognathic surgery, dental splints are important and necessary to help the surgeon reposition the maxilla or mandible. However, the traditional methods of manual design of dental splints are difficult and time-consuming. The research on computer-aided design software for dental splints is rarely reported. Ou...
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Energy-transport systems for optical lattices: derivation, analysis, simulation
Energy-transport equations for the transport of fermions in optical lattices are formally derived from a Boltzmann transport equation with a periodic lattice potential in the diffusive limit. The limit model possesses a formal gradient-flow structure like in the case of the energy-transport equations for semiconducto...
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First principles study of structural, magnetic and electronic properties of CrAs
We report ab initio density functional calculations of the structural and magnetic properties, and the electronic structure of CrAs. To simulate the observed pressure-driven experimental results, we perform our analysis for different volumes of the unit cell, showing that the structural, magnetic and electronic prope...
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Subspace Robust Wasserstein distances
Making sense of Wasserstein distances between discrete measures in high-dimensional settings remains a challenge. Recent work has advocated a two-step approach to improve robustness and facilitate the computation of optimal transport, using for instance projections on random real lines, or a preliminary quantization ...
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Wind accretion onto compact objects
X-ray emission associated to accretion onto compact objects displays important levels of photometric and spectroscopic time-variability. When the accretor orbits a Supergiant star, it captures a fraction of the supersonic radiatively-driven wind which forms shocks in its vicinity. The amplitude and stability of this ...
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Riemannian Stein Variational Gradient Descent for Bayesian Inference
We develop Riemannian Stein Variational Gradient Descent (RSVGD), a Bayesian inference method that generalizes Stein Variational Gradient Descent (SVGD) to Riemann manifold. The benefits are two-folds: (i) for inference tasks in Euclidean spaces, RSVGD has the advantage over SVGD of utilizing information geometry, an...
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Suspension-thermal noise in spring-antispring systems for future gravitational-wave detectors
Spring-antispring systems have been investigated as possible low-frequency seismic isolation in high-precision optical experiments. These systems provide the possibility to tune the fundamental resonance frequency to, in principle, arbitrarily low values, and at the same time maintain a compact design of the isolatio...
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